1.0 What's Python

Python is written in C (actually the default implementation is called CPython)

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Types of Python objects:

Integers can be negative or positive numbers. Floats are real numbers (a superset of integers, including numbers with decimals)

Check type of a variable with the type() function:

1.1 Expressions are operations among compatible data types.

1.2 Storing variables in Python is quite easy. We can also perform operation on the stored variables.

1.3 Conditions and Branching

1.4 Loops

1.5 Functions

1.6 Objects and classes

2.0 Numpy

Numpy solves one essential problem very fast: array processing

It is also very fast with problems that are naturally vectorized, like matrix multiplication and linear algebra routines, vectors generation and application of fixed transformation over entire array.

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2.1 Shape and dimensions

2.1.1 Create arrays in memory that can later be populated with data\

2.1.2 Set an array of eventy spaced numbers

2.1.3 Create an identity matrix

2.1.4 Create array from python list

2.1.5 Array indexing

2.2 2D arrays operations

2.2.1 Indexing

2.2.2 Extract columns and rows

2.3 Array methods

2.3.1 mean, sort, sum, etc.

2.3.2 Indexing

2.3.3 Array operations

2.4 Operations on 2D array

2.4.1 Vectorized funcitons

2.4.2 Comparisons

3.0 Pandas

Pandas is a module for fast and efficient data analysis tools in Python.

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3.1 Loading DataFrames

3.2 Using DFs

3.2 DataFrame columns

3.3 DF operations

3.3 Lazy Plots

4.0 Plotly

4.1 Bars

4.2 Scatters

4.3 Regplots

4.4 Histogram

4.5 3D Graphs

4.6 Git gud!

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5.0 Modeling

5.1 File 1

5.2 File 2

5.3 File 3

5.4 File 4

5.5 Final output

5.6 X & Y

5.7 Regression

5.8 Back to da drawing board

5.9 Data cleaning

5.10 Model 2

5.11 Feature importance

5.12 Does life have meaning?